三维对象表示的神经网络体系结构

The 2nd IEEE Internatioal Workshop on Haptic, Audio and Visual Environments and Their Applications, 2003. HAVE 2003. Proceedings. Pub Date : 2003-11-10 DOI:10.1109/HAVE.2003.1244721

A. Crétu, E. Petriu, G. Patry

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引用次数: 12

摘要

本文讨论了一种用于三维物体建模的神经网络体系结构。采用以目标点的三维坐标为输入的多层前馈结构对目标空间进行建模。与转换神经网络模块级联，所提出的体系结构可用于生成和训练3D对象，执行转换，设置操作和对象变形。并提出了一种可能的目标识别应用。

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Neural network architecture for 3D object representation

The paper discusses a neural network architecture for 3D object modeling. A multi-layered feedforward structure having as inputs the 3D-coordinates of the object points is employed to model the object space. Cascaded with a transformation neural network module, the proposed architecture can be used to generate and train 3D objects, perform transformations, set operations and object morphing. A possible application for object recognition is also presented.

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The 2nd IEEE Internatioal Workshop on Haptic, Audio and Visual Environments and Their Applications, 2003. HAVE 2003. Proceedings.

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